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COVID-19 Impact on Global Machine Learning (ML) Platforms Market Size, Status and Forecast 2020-2026

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1 Report Overview

  • 1.1 Study Scope
  • 1.2 Key Market Segments
  • 1.3 Market Analysis by Type
    • 1.3.1 Global Machine Learning (ML) Platforms Market Size Growth Rate by Type: 2020 VS 2026
    • 1.3.2 Cloud-based
    • 1.3.3 On-premises
  • 1.4 Market by Application
    • 1.4.1 Global Machine Learning (ML) Platforms Market Share by Application: 2020 VS 2026
    • 1.4.2 Small and Medium Enterprises (SMEs)
    • 1.4.3 Large Enterprises
  • 1.5 Study Objectives
  • 1.6 Years Considered

2 Global Growth Trends

  • 2.1 Global Machine Learning (ML) Platforms Market Perspective (2015-2026)
  • 2.2 Machine Learning (ML) Platforms Growth Trends by Regions
    • 2.2.1 Machine Learning (ML) Platforms Market Size by Regions: 2015 VS 2020 VS 2026
    • 2.2.2 Machine Learning (ML) Platforms Historic Market Share by Regions (2015-2020)
    • 2.2.3 Machine Learning (ML) Platforms Forecasted Market Size by Regions (2021-2026)
  • 2.3 Machine Learning (ML) Platforms Industry Dynamic
    • 2.3.1 Machine Learning (ML) Platforms Market Trends
    • 2.3.2 Machine Learning (ML) Platforms Market Drivers
    • 2.3.3 Machine Learning (ML) Platforms Market Challenges
    • 2.3.4 Machine Learning (ML) Platforms Market Restraints

3 Competition Landscape by Key Players

  • 3.1 Global Top Machine Learning (ML) Platforms Players by Market Size
    • 3.1.1 Global Top Machine Learning (ML) Platforms Players by Revenue (2015-2020)
    • 3.1.2 Global Machine Learning (ML) Platforms Revenue Market Share by Players (2015-2020)
  • 3.2 Global Machine Learning (ML) Platforms Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
  • 3.3 Players Covered: Ranking by Machine Learning (ML) Platforms Revenue
  • 3.4 Global Machine Learning (ML) Platforms Market Concentration Ratio
    • 3.4.1 Global Machine Learning (ML) Platforms Market Concentration Ratio (CR5 and HHI)
    • 3.4.2 Global Top 10 and Top 5 Companies by Machine Learning (ML) Platforms Revenue in 2019
  • 3.5 Key Players Machine Learning (ML) Platforms Area Served
  • 3.6 Key Players Machine Learning (ML) Platforms Product Solution and Service
  • 3.7 Date of Enter into Machine Learning (ML) Platforms Market
  • 3.8 Mergers & Acquisitions, Expansion Plans

4 Machine Learning (ML) Platforms Breakdown Data by Type

  • 4.1 Global Machine Learning (ML) Platforms Historic Market Size by Type (2015-2020)
  • 4.2 Global Machine Learning (ML) Platforms Forecasted Market Size by Type (2021-2026)

5 Machine Learning (ML) Platforms Breakdown Data by Application

  • 5.1 Global Machine Learning (ML) Platforms Historic Market Size by Application (2015-2020)
  • 5.2 Global Machine Learning (ML) Platforms Forecasted Market Size by Application (2021-2026)

6 North America

  • 6.1 North America Machine Learning (ML) Platforms Market Size (2015-2026)
  • 6.2 North America Machine Learning (ML) Platforms Market Size by Type (2015-2020)
  • 6.3 North America Machine Learning (ML) Platforms Market Size by Application (2015-2020)
  • 6.4 North America Machine Learning (ML) Platforms Market Size by Country (2015-2020)
    • 6.4.1 United States
    • 6.4.2 Canada

7 Europe

  • 7.1 Europe Machine Learning (ML) Platforms Market Size (2015-2026)
  • 7.2 Europe Machine Learning (ML) Platforms Market Size by Type (2015-2020)
  • 7.3 Europe Machine Learning (ML) Platforms Market Size by Application (2015-2020)
  • 7.4 Europe Machine Learning (ML) Platforms Market Size by Country (2015-2020)
    • 7.4.1 Germany
    • 7.4.2 France
    • 7.4.3 U.K.
    • 7.4.4 Italy
    • 7.4.5 Russia
    • 7.4.6 Nordic

8 Asia-Pacific

  • 8.1 Asia-Pacific Machine Learning (ML) Platforms Market Size (2015-2026)
  • 8.2 Asia-Pacific Machine Learning (ML) Platforms Market Size by Type (2015-2020)
  • 8.3 Asia-Pacific Machine Learning (ML) Platforms Market Size by Application (2015-2020)
  • 8.4 Asia-Pacific Machine Learning (ML) Platforms Market Size by Region (2015-2020)
    • 8.4.1 China
    • 8.4.2 Japan
    • 8.4.3 South Korea
    • 8.4.4 Southeast Asia
    • 8.4.5 India
    • 8.4.6 Australia

9 Latin America

  • 9.1 Latin America Machine Learning (ML) Platforms Market Size (2015-2026)
  • 9.2 Latin America Machine Learning (ML) Platforms Market Size by Type (2015-2020)
  • 9.3 Latin America Machine Learning (ML) Platforms Market Size by Application (2015-2020)
  • 9.4 Latin America Machine Learning (ML) Platforms Market Size by Country (2015-2020)
    • 9.4.1 Mexico
    • 9.4.2 Brazil

10 Middle East & Africa

  • 10.1 Middle East & Africa Machine Learning (ML) Platforms Market Size (2015-2026)
  • 10.2 Middle East & Africa Machine Learning (ML) Platforms Market Size by Type (2015-2020)
  • 10.3 Middle East & Africa Machine Learning (ML) Platforms Market Size by Application (2015-2020)
  • 10.4 Middle East & Africa Machine Learning (ML) Platforms Market Size by Country (2015-2020)
    • 10.4.1 Turkey
    • 10.4.2 Saudi Arabia
    • 10.4.3 UAE

11Key Players Profiles

  • 11.1 Palantier
    • 11.1.1 Palantier Company Details
    • 11.1.2 Palantier Business Overview
    • 11.1.3 Palantier Machine Learning (ML) Platforms Introduction
    • 11.1.4 Palantier Revenue in Machine Learning (ML) Platforms Business (2015-2020))
    • 11.1.5 Palantier Recent Development
  • 11.2 MathWorks
    • 11.2.1 MathWorks Company Details
    • 11.2.2 MathWorks Business Overview
    • 11.2.3 MathWorks Machine Learning (ML) Platforms Introduction
    • 11.2.4 MathWorks Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.2.5 MathWorks Recent Development
  • 11.3 Alteryx
    • 11.3.1 Alteryx Company Details
    • 11.3.2 Alteryx Business Overview
    • 11.3.3 Alteryx Machine Learning (ML) Platforms Introduction
    • 11.3.4 Alteryx Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.3.5 Alteryx Recent Development
  • 11.4 SAS
    • 11.4.1 SAS Company Details
    • 11.4.2 SAS Business Overview
    • 11.4.3 SAS Machine Learning (ML) Platforms Introduction
    • 11.4.4 SAS Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.4.5 SAS Recent Development
  • 11.5 Databricks
    • 11.5.1 Databricks Company Details
    • 11.5.2 Databricks Business Overview
    • 11.5.3 Databricks Machine Learning (ML) Platforms Introduction
    • 11.5.4 Databricks Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.5.5 Databricks Recent Development
  • 11.6 TIBCO Software
    • 11.6.1 TIBCO Software Company Details
    • 11.6.2 TIBCO Software Business Overview
    • 11.6.3 TIBCO Software Machine Learning (ML) Platforms Introduction
    • 11.6.4 TIBCO Software Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.6.5 TIBCO Software Recent Development
  • 11.7 Dataiku
    • 11.7.1 Dataiku Company Details
    • 11.7.2 Dataiku Business Overview
    • 11.7.3 Dataiku Machine Learning (ML) Platforms Introduction
    • 11.7.4 Dataiku Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.7.5 Dataiku Recent Development
  • 11.8 H2O.ai
    • 11.8.1 H2O.ai Company Details
    • 11.8.2 H2O.ai Business Overview
    • 11.8.3 H2O.ai Machine Learning (ML) Platforms Introduction
    • 11.8.4 H2O.ai Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.8.5 H2O.ai Recent Development
  • 11.9 IBM
    • 11.9.1 IBM Company Details
    • 11.9.2 IBM Business Overview
    • 11.9.3 IBM Machine Learning (ML) Platforms Introduction
    • 11.9.4 IBM Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.9.5 IBM Recent Development
  • 11.10 Microsoft
    • 11.10.1 Microsoft Company Details
    • 11.10.2 Microsoft Business Overview
    • 11.10.3 Microsoft Machine Learning (ML) Platforms Introduction
    • 11.10.4 Microsoft Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 11.10.5 Microsoft Recent Development
  • 11.11 Google
    • 10.11.1 Google Company Details
    • 10.11.2 Google Business Overview
    • 10.11.3 Google Machine Learning (ML) Platforms Introduction
    • 10.11.4 Google Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.11.5 Google Recent Development
  • 11.12 KNIME
    • 10.12.1 KNIME Company Details
    • 10.12.2 KNIME Business Overview
    • 10.12.3 KNIME Machine Learning (ML) Platforms Introduction
    • 10.12.4 KNIME Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.12.5 KNIME Recent Development
  • 11.13 DataRobot
    • 10.13.1 DataRobot Company Details
    • 10.13.2 DataRobot Business Overview
    • 10.13.3 DataRobot Machine Learning (ML) Platforms Introduction
    • 10.13.4 DataRobot Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.13.5 DataRobot Recent Development
  • 11.14 RapidMiner
    • 10.14.1 RapidMiner Company Details
    • 10.14.2 RapidMiner Business Overview
    • 10.14.3 RapidMiner Machine Learning (ML) Platforms Introduction
    • 10.14.4 RapidMiner Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.14.5 RapidMiner Recent Development
  • 11.15 Anaconda
    • 10.15.1 Anaconda Company Details
    • 10.15.2 Anaconda Business Overview
    • 10.15.3 Anaconda Machine Learning (ML) Platforms Introduction
    • 10.15.4 Anaconda Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.15.5 Anaconda Recent Development
  • 11.16 Domino
    • 10.16.1 Domino Company Details
    • 10.16.2 Domino Business Overview
    • 10.16.3 Domino Machine Learning (ML) Platforms Introduction
    • 10.16.4 Domino Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.16.5 Domino Recent Development
  • 11.17 Altair
    • 10.17.1 Altair Company Details
    • 10.17.2 Altair Business Overview
    • 10.17.3 Altair Machine Learning (ML) Platforms Introduction
    • 10.17.4 Altair Revenue in Machine Learning (ML) Platforms Business (2015-2020)
    • 10.17.5 Altair Recent Development

12Analyst's Viewpoints/Conclusions

    13Appendix

    • 13.1 Research Methodology
      • 13.1.1 Methodology/Research Approach
      • 13.1.2 Data Source
    • 13.2 Disclaimer

    Market Analysis and Insights: Global Machine Learning (ML) Platforms Market
    The global Machine Learning (ML) Platforms market size is projected to reach US$ XX million by 2026, from US$ XX million in 2020, at a CAGR of XX% during 2021-2026.
    With industry-standard accuracy in analysis and high data integrity, the report makes a brilliant attempt to unveil key opportunities available in the global Machine Learning (ML) Platforms market to help players in achieving a strong market position. Buyers of the report can access verified and reliable market forecasts, including those for the overall size of the global Machine Learning (ML) Platforms market in terms of revenue.
    On the whole, the report proves to be an effective tool that players can use to gain a competitive edge over their competitors and ensure lasting success in the global Machine Learning (ML) Platforms market. All of the findings, data, and information provided in the report are validated and revalidated with the help of trustworthy sources. The analysts who have authored the report took a unique and industry-best research and analysis approach for an in-depth study of the global Machine Learning (ML) Platforms market.
    Machine Learning (ML) Platforms Breakdown Data by Type
    Cloud-based
    On-premises
    Machine Learning (ML) Platforms Breakdown Data by Application
    Small and Medium Enterprises (SMEs)
    Large Enterprises
    Based on regional and country-level analysis, the Machine Learning (ML) Platforms market has been segmented as follows:
    North America
    United States
    Canada
    Europe
    Germany
    France
    U.K.
    Italy
    Russia
    Nordic
    Rest of Europe
    Asia-Pacific
    China
    Japan
    South Korea
    Southeast Asia
    India
    Australia
    Rest of Asia-Pacific
    Latin America
    Mexico
    Brazil
    Middle East & Africa
    Turkey
    Saudi Arabia
    UAE
    Rest of Middle East & Africa
    In the competitive analysis section of the report, leading as well as prominent players of the global Machine Learning (ML) Platforms market are broadly studied on the basis of key factors. The report offers comprehensive analysis and accurate statistics on revenue by the player for the period 2015-2020. It also offers detailed analysis supported by reliable statistics on price and revenue (global level) by player for the period 2015-2020.
    The following players are covered in this report:
    Palantier
    MathWorks
    Alteryx
    SAS
    Databricks
    TIBCO Software
    Dataiku
    H2O.ai
    IBM
    Microsoft
    Google
    KNIME
    DataRobot
    RapidMiner
    Anaconda
    Domino
    Altair
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